Feasibility of a Deep Learning-based Algorithm for Non-invasive Assessment of Vulnerable Coronary Plaque
NCT06186336 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 200
Last updated 2025-01-07
Summary
The primary objective of this study is to assess the accuracy in terms of sensitivity, specificity, negative and positive predicted values of the DL-based algorithm with respect to correct identification of the plaque and associated vulnerability grade.
Conditions
- Chronic Coronary Syndrome
- Coronary Artery Disease
- Stable Angina
- Acute Coronary Syndrome
Interventions
- OTHER
-
Deep Learning-based Vulnerable Plaque Detection and Assessment Tool
Scanning requirements for the clinically indicated CCTA and ICA with OCT will be performed according to current site(s) guidelines and procedures. Administration of medications (such as contrast agents and potentially beta-blockers and other medications) will be given according to standard hospital care. This is a prospective research study evaluating an investigational product. The tool's use is intended for research purposes and is not intended as a substitute for required medical care. The CCTA and ICA with OCT will be processed in real-time using the site's locally available post-processing tools in order to guide the subject's medical care. Once the ICA with OCT is complete, the de-identified CCTA data will be inputted in the investigational tool. The clinically indicated CCTA and the ICA with OCT will both take approximately 1 hour and will take place within 10 days. No additional imaging is needed as part of the study.
Sponsors & Collaborators
-
Azienda Socio-Sanitaria Territoriale di Pavia
collaborator UNKNOWN -
GE Healthcare
lead INDUSTRY
Principal Investigators
-
Paul Deak · GE Healthcare
Eligibility
- Sex
- ALL
- Healthy Volunteers
- No
Timeline & Regulatory
- Start
- 2025-01-31
- Primary Completion
- 2025-06-30
- Completion
- 2025-06-30
Countries
- Italy
Study Locations
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